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Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches.

Christian GünzelFelix KühnlKatharina ArnoldSven FindeißChristina E WeinbergPeter F StadlerMario Mörl
Published in: RNA biology (2020)
Gene regulation in prokaryotes often depends on RNA elements such as riboswitches or RNA thermometers located in the 5' untranslated region of mRNA. Rearrangements of the RNA structure in response, e.g., to the binding of small molecules or ions control translational initiation or premature termination of transcription and thus mRNA expression. Such structural responses are amenable to computational modelling, making it possible to rationally design synthetic riboswitches for a given aptamer. Starting from an artificial aptamer, we construct the first synthetic transcriptional riboswitches that respond to the antibiotic neomycin. We show that the switching behaviour in vivo critically depends not only on the sequence of the riboswitch itself, but also on its sequence context. We therefore developed in silico methods to predict the impact of the context, making it possible to adapt the design and to rescue non-functional riboswitches. We furthermore analyse the influence of 5' hairpins with varying stability on neomycin riboswitch activity. Our data highlight the limitations of a simple plug-and-play approach in the design of complex genetic circuits and demonstrate that detailed computational models significantly simplify, improve, and automate the design of transcriptional circuits. Our design software is available under a free licence on GitHub (https://github.com/xileF1337/riboswitch_design).
Keyphrases
  • gene expression
  • transcription factor
  • machine learning
  • electronic health record
  • sensitive detection
  • binding protein
  • quantum dots
  • big data
  • deep learning
  • amino acid
  • dna binding
  • label free
  • copy number